Single-cell Molecular Analysis Research Articles

Skeletal stem and progenitor cells in bone development and repair.

Bone development, growth, and repair are complex processes involving various cell types and interactions, with central roles played by skeletal stem and progenitor cells. Recent research brought new insights into the skeletal precursor populations that mediate intramembranous and endochondral bone development. Later in life, many of the cellular and molecular mechanisms determining development are reactivated upon fracture, with powerful trauma-induced signaling cues triggering a variety of postnatal skeletal stem/progenitor cells (SSPCs) residing near the bone defect. Interestingly, in this injury context, the current evidence suggests that the fates of both SSPCs and differentiated skeletal cells can be considerably flexible and dynamic, and that multiple cell sources can be activated to operate as functional progenitors generating chondrocytes and/or osteoblasts. The combined implementation of in vivo lineage tracing, cell surface marker-based cell selection, single-cell molecular analyses, and high-resolution in situ imaging has strongly improved our insights into the diversity and roles of developmental and reparative stem/progenitor subsets, while also unveiling the complexity of their dynamics, hierarchies, and relationships. Albeit incompletely understood at present, findings supporting lineage flexibility and possibly plasticity among sources of osteogenic cells challenge the classical dogma of a single primitive, self-renewing, multipotent stem cell driving bone tissue formation and regeneration from the apex of a hierarchical and strictly unidirectional differentiation tree. We here review the state of the field and the newest discoveries in the origin, identity, and fates of skeletal progenitor cells during bone development and growth, discuss the contributions of adult SSPC populations to fracture repair, and reflect on the dynamism and relationships among skeletal precursors and differentiated cell lineages. Further research directed at unraveling the heterogeneity and capacities of SSPCs, as well as the regulatory cues determining their fate and functioning, will offer vital new options for clinical translation toward compromised fracture healing and bone regenerative medicine.

Abstract 3709: Single cell analysis from CSF of patients with suspected leptomeningeal metastasis

Abstract Introduction: Leptomeningeal metastases (LM) are diagnosed in up to 10% of metastatic cancer patients, the most frequent cancers being carcinomas of breast and lung or melanoma. Due to a dismal prognosis and an overall median survival of only four months new approaches for molecular analysis could help to identify individual treatment options. Material and Methods: In this study, we collected 28 cerebrospinal fluid (CSF) samples from patients with different primary tumors but suspected LM. CSF was divided in two parts for standard neuropathologic cytomorphology and detection of circulating tumor cells (CTCs) by using the CellSearch® CTC Kit, respectively. Subsequently, single Cytokeratin-positive CTCs were isolated for whole genome amplification by Ampli1TM and molecular analysis. Additionally, we were able to isolate cell-free DNA (cfDNA) from CSF in a subset of patients which we amplified by an adapted Ampli1TM library protocol. In a small subset of patients, we collected slices of formalin-fixed paraffin embedded (FFPE) primary tumors and systemic metastases for dissociation and isolation of pure subpopulations by DEPArrayTM technology. Isolated CTCs, cfDNA and subpopulations of tumor and stromal cells were analyzed for copy number variations (CNV) applying the Ampli1TM LowPass protocol on the Illumina MiSeqTM platform. Results: By comparing results from classical cytomorphology and CellSearch® workflow, we could find high concordance (24/28 samples) with a slightly higher tumor cell detection rate by CellSearch® (11 positive cases vs. 9 by cytomorphology). Importantly, we could confirm the malignant origin of isolated cells by CNV analysis in all patients positive in CellSearch® assay. Moreover, by comparing single cell data with cfDNA analysis of a subset of 20 samples, we could also detect a higher sensitivity for tumor detection in CTC-based analysis (8/20 cases positive) in comparison to cfDNA-based analysis (5/20 cases positive). In a comprehensive analysis of multiple samples of an individual patient, including CTCs and cfDNA from CSF at different time points, CTCs from blood and biopsies from multiple visceral metastasis, we could identify divergent genomic evolution between tumor cells from the central nervous syste Conclusion: In this proof-of-concept study we show that a liquid biopsy-based approach for single cell analysis from CSF holds potential for innovative diagnostic assays for patients with suspected LM. Combining CTC quantification with molecular single cell analysis could enable us to define predictive tests to select novel treatment options for patients with LM in the future. Citation Format: Caecilia Koestler, Giancarlo Feliciello, Florian Lueke, Kathrin Weidele, Saida Zoubaa, Peter Hau, Tobias Pukrop, Markus J. Riemenschneider, Christoph A. Klein, Bernhard Polzer. Single cell analysis from CSF of patients with suspected leptomeningeal metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3709.

Immunophenotypic characterization of leukemic stem cells in acute myeloid leukemia using single tube 10-colour panel by multiparametric flow cytometry: Deciphering the spectrum, complexity and immunophenotypic heterogeneity.

Despite extensive research, comprehensive characterization of leukaemic stem cells (LSC) and information on their immunophenotypic differences from normal haematopoietic stem cells (HSC) is lacking. Herein, we attempted to unravel the immunophenotypic (IPT) characteristics and heterogeneity of LSC using multiparametric flow cytometry (MFC) and single-cell sequencing. Bone marrow aspirate samples from patients with acute myeloid leukaemia (AML) were evaluated using MFC at diagnostic and post induction time points using a single tube-10-colour-panel containing LSC-associated antibodies CD123, CD45RA, CD44, CD33 and COMPOSITE (CLL-1, TIM-3, CD25, CD11b, CD22, CD7, CD56) with backbone markers that is, CD45, CD34, CD38, CD117, sCD3. Single-cell sequencing of the whole transcriptome was also done in a bone marrow sample. LSCs and HSCs were identified in 225/255 (88.2%) and 183/255 (71.6%) samples, respectively. Significantly higher expression was noted for COMPOSITE, CD45RA, CD123, CD33, and CD44 in LSCs than HSCs (p < 0.0001). On comparing the LSC specific antigen expressions between CD34+ (n = 184) and CD34- LSCs (n = 41), no difference was observed between the groups. More than one sub-population of LSC was demonstrated in 4.4% of cases, which further revealed high concordance between MFC and single cell transcriptomic analysis in one of the cases displaying three LSC subpopulations by both methods. A single tube-10-colour MFC panel is proposed as an easy and reproducible tool to identify and discriminate LSCs from HSCs. LSCs display both inter- and intra-sample heterogeneity in terms of antigen expressions, which opens the facets for single cell molecular analysis to elucidate the role of subpopulations of LSCs in AML progression.

Immunoblot Analysis from Single Cells Using Milo™ Single-Cell Western Platform.

In this new era of precision medicine, characterization of single-cell subpopulations to better understand disease etiology is paramount. It is thus an opportune time to explore techniques that allow molecular analysis of single cells and to better understand the basis of pathogenesis of diseases like cancer. Single-cell western blotting is one such method that allows analysis of single cells at the protein level. In contrast to traditional western blotting, which relies heavily on bulk analysis of lysates generated from tissues and is often indicative of the population average, this technique allows analysis of lysates from single-cell subpopulations thereby providing a glimpse into cell heterogeneity. The method entails the use of a chip containing 30μm thick photoactivated polyacrylamide gel spotted with nearly 6400 microwells. Single cells loaded on the chip are captured in the microwells by passive gravity and are then lysed and electrophoresed using the MILO™ single-cell western platform. This method forgoes the use of transfer of proteins on a PVDF and a nitrocellulose membrane, as performed in traditional western blotting, and all other steps including probing of primary and fluorescent secondary antibodies against the protein of interest are performed directly on the chip. The proteins of interest can then be visualized by scanning a chip with the use of a microarray scanner. The entire procedure can be performed in as less as 4-6h, and thus this method provides several advantages over traditional western blotting.

Some Aspects of the Physiology of the Nyctotherus velox, a Commensal Ciliated Protozoon Taken from the Hindgut of the Tropical Millipede Archispirostreptus gigas.

In this paper, the growth requirements, fermentation pattern, and hydrolytic enzymatic activities of anaerobic ciliates collected from the hindgut of the African tropical millipede Archispirostreptus gigas are described. Single-cell molecular analysis showed that ciliates from the millipede hindgut could be assigned to the Nyctotherus velox and a new species named N. archispirostreptae n. sp. The ciliate N. velox can grow in vitro with unspecified prokaryotic populations and various plant polysaccharides (rice starch-RS, xylan, crystalline cellulose20-CC, carboxymethylcellulose-CMC, and inulin) or without polysaccharides (NoPOS) in complex reduced medium with soluble supplements (peptone, glucose, and vitamins). Specific catalytic activity (nkat/g of protein) of α amylase of 300, xylanase of 290, carboxymethylcellulase of 190, and inulinase of 170 was present in the crude protein extract of N. velox. The highest in vitro dry matter digestibility was observed in RS and inulin after 96 h of fermentation. The highest methane concentration was observed in xylan and inulin substrates. The highest short-chain fatty acid concentration was observed in RS, inulin, and xylan. In contrast, the highest ammonia concentration was observed in NoPOS, CMC, and CC. The results indicate that starch is the preferred substrate of the N. velox. Hydrolytic enzyme activities of N. velox showed that the ciliates contribute to the fermentation of plant polysaccharides in the gut of millipedes.

Abstract 5447: Artificial intelligence (AI)-based classification of stromal subtypes reveals associations between stromal composition and prognosis in NSCLC

Abstract Background: Many cancers are known to involve a desmoplastic stromal reaction. While cancer-associated stroma (CAS) has long been appreciated histologically, single-cell molecular analyses have revealed its heterogeneity, and the cellular composition of CAS has been linked to prognosis in several cancer types, including NSCLC. While pathologists have sought to manually classify CAS based on collagen architecture or nuclear density, this approach has not sufficiently captured the heterogeneity of CAS. To this end, we have developed an artificial intelligence (AI)-based model to predict stromal composition in NSCLC from hematoxylin and eosin (H&amp;E)-stained tissue Methods: We developed a convolutional neural network-based model to classify CAS as immature, mature, densely inflamed, densely fibroblastic, or elastosis. This model was trained using manual pathologist-derived annotations (N=3019) of H&amp;E-stained whole slide images (WSIs) of PDAC obtained from the TCGA (N=126). This stromal subdivision model was deployed on H&amp;E-stained LUAD (N=468) and LUSC (N=430) WSIs. Model performance was assessed by qualitative review by expert pathologists. Human interpretable features (HIFs) were extracted from the stromal subdivision model (e.g., proportional area of mature relative to total stroma) and were assessed to identify associations with overall survival (OS) using univariate Cox regression analysis after adjusting for age, sex, and tumor stage. Results: The stromal subdivision model successfully predicted areas of immature, mature, densely inflammatory, and densely fibrotic stroma, as well as elastosis, in LUAD and LUSC. In LUAD, higher combined proportional areas of mature and fibroblastic stroma relative to total cancer stroma was associated with poor OS (p=0.007), while higher combined proportional areas of densely inflamed stroma and elastosis relative to total cancer stroma was associated with improved OS (p=0.007). These findings were validated by stratified tertile analysis based on the corresponding risk direction. Notably, while the average stromal compositions did not differ significantly between NSCLC subtypes, the stromal HIFs were only prognostic in LUAD but not in LUSC. Conclusions: We developed a first of its kind model to characterize CAS subtypes in NSCLC tissue. Features extracted from this model are related to prognosis in LUAD, but not in LUSC, further confirming the importance of CAS to tumor biology and the importance of considering histologic subtypes. Work is ongoing to identify relationships between stromal HIFs and treatment response in NSCLC as well as other cancer indications. Citation Format: Fedaa Najdawi, Sandhya Srinivasan, Neel Patel, Michael G. Drage, Christian Kirkup, Chintan Parmar, Jacqueline Brosnan-Cashman, Michael Montalto, Andrew H. Beck, Archit Khosla, Ilan Wapinski, Ben Glass, Murray Resnick, Matthew Bronnimann. Artificial intelligence (AI)-based classification of stromal subtypes reveals associations between stromal composition and prognosis in NSCLC. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5447.

High activation levels maintained in receptor-binding domain-specific memory B cells in people with severe coronavirus disease 2019.

The long-term health consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are still being understood. The molecular and phenotypic properties of SARS-CoV-2 antigen-specific T cells suggest a dysfunctional profile that persists in convalescence in those who were severely ill. By contrast, the antigen-specific memory B-cell (MBC) population has not yet been analyzed to the same degree, but phenotypic analysis suggests differences following recovery from mild or severe coronavirus disease 2019 (COVID-19). Here, we performed single-cell molecular analysis of the SARS-CoV-2 receptor-binding domain (RBD)-specific MBC population in three patients after severe COVID-19 and four patients after mild/moderate COVID-19. We analyzed the transcriptomic and B-cell receptor repertoire profiles at ~2 months and ~4 months after symptom onset. Transcriptomic analysis revealed a higher level of tumor necrosis factor-alpha (TNF-α) signaling via nuclear factor-kappa B in the severe group, involving CD80, FOS, CD83 and TNFAIP3 genes that was maintained over time. We demonstrated the presence of two distinct activated MBCs subsets based on expression of CD80hi TNFAIP3hi and CD11chi CD95hi at the transcriptome level. Both groups revealed an increase in somatic hypermutation over time, indicating progressive evolution of humoral memory. This study revealed distinct molecular signatures of long-term RBD-specific MBCs in convalescence, indicating that the longevity of these cells may differ depending on acute COVID-19 severity.

Partial advances in the diagnosis and treatment of gastrointestinal cancer.

Partial advances in the diagnosis and treatment of gastrointestinal cancer.

Stem Cells, Hematopoiesis and Lineage Tracing: Transplantation-Centric Views and Beyond.

An appropriate production of mature blood cells, or hematopoiesis, is essential for organismal health and homeostasis. In this developmental cascade, hematopoietic stem cells (HSCs) differentiate into intermediate progenitor types, that subsequently give rise to the many distinct blood cell lineages. Here, we describe tools and methods that permit for temporal and native clonal-level HSC lineage tracing in the mouse, and that can now be combined with emerging single-cell molecular analyses. We integrate new insights derived from such experimental paradigms with past knowledge, which has predominantly been derived from transplantation-based approaches. Finally, we outline current knowledge and novel strategies derived from studies aimed to trace human HSC-derived hematopoiesis.

Traceable impedance-based single-cell pipetting, from a research set-up to a robust and fast automated robot: DispenCell-S1.

Single-cell isolation is a truly transformative tool for the understanding of biological systems. It allows single-cell molecular analyses and considers the heterogeneity of cell populations, which is of particular relevance for the diagnosis and treatment of evolving diseases and for personalized medicine. Single-cell isolation is also a key process in cell line development, where it is used to obtain stable and high producing clonally-derived cell lines, thus contributing to the efficiency, safety and reproducible quality of the drug produced. High producing clonally-derived cell lines are however rare events and their identification is a time-consuming process that requires the screening of thousands of clones. Therefore, there is an unmet need for a device that would allow the fast and efficient isolation of single cells, while preserving their integrity and providing an insurance of their clonality. We proposed earlier an impedance based pipetting technology for isolation of single cells (Bonzon etal., 2020), with initial validations for state-of-the-art stem cell in-vitro and in-vivo assays (Muller etal., 2020). Here, we present the transition from this pioneering technology developed in an academic setting into an automated instrument, called DispenCell-S1, allowing for traceable isolation of single cells. We developed and validated models predicting the performances for 96-well plates single-cell isolation. This resulted in a time of dispense down to 3min and a plate filling rate up to 96%. Finally, we obtained an impedance signal reliability for proof of single particle isolation of 99% with beads and ranging from 93 to 95% with CHO cells.

A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer

We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their positions in a solid tissue do not apply. Our design consists of two parts, as follows: recording 3D cell images at high throughput (500 to 1,000 cells/s) using a custom 3D imaging flow cytometer (3D-IFC) and dispensing cells in a first-in-first-out (FIFO) manner using a robotic cell placement platform (CPP). To prevent errors due to violations of the FIFO principle, we invented a method that uses marker beads and DNA sequencing software to detect errors. Experiments with human cancer cell lines demonstrate the feasibility of mapping 3D side scattering and fluorescent images, as well as two-dimensional (2D) transmission images of cells to their locations on the membrane filter for around 100,000 cells in less than 10 min. While the current work uses our specially designed 3D imaging flow cytometer to produce 3D cell images, our methodology can support other imaging modalities. The technology and method form a bridge between single-cell image analysis and single-cell molecular analysis.

Abstract P2-02-06: Her2-low ctcs in breast cancer: Pipeline for phenotypic driven, single-cell collection and molecular analysis

Abstract Background The presence of circulating tumor cells (CTCs) expressing HER2 at low score (HER2-low) in the peripheral blood of metastatic breast cancer (MBC) patients has been associated with resistance to treatment and more aggressive metastatic behavior. However, the biological intrinsic nature of HER2-low CTCs remains unexplored. Considering the technical challenges beyond the selective collection of immunophenotype-specific CTCs, we developed a pipeline to individually capture HER2-low CTCs to perform single-cell molecular analysis. Methods 4 different breast cancer cell lines (MDA-MB-231, T47D, MDA-MB-453, SKBR3), that are known to express HER2 at different immunohistochemistry scores (respectively classified as 0, 1+, 2+, 3+), were spiked (around 500 cells each) in healthy donor blood tubes (7.5 ml). Samples were subsequently enriched through the CellSearch™ (Menarini Silicon Biosystems, Bologna, Italy), HER2 stained using the CellSearch CTC Kit and analyzed with the ACCEPT tool (Zeune et al., 2017). Enriched cells were additionally characterized by the DEPArray NxT™ Cell Browser and subsequently collected in pooled and single cells. The HER2 signal-intensity scores (fluorescein isothiocyanate, FITC mean), detected by both tools in each cell line, was compared using the nonparametric Mann-Whitney U test. The optimal cut-offs to distinguish HER2 1+ from HER2 0 and HER2 2+ cells were calculated performing Receiving Operator Curves (ROC). Results Detected mean intensities retrieved from CellSearch™ and analyzed with the ACCEPT tool were respectively 0.34 (MDA-MB-231, 0), 1.44 (T47D, 1+), 15.28 (MDA-MB-453, 2+) 166 (SKBR3, 3+), resulting in the possibility to discriminate both 2+ and 3+ cells from 1+ and 0 (P &amp;lt; 0.00001). No statistical significance has been observed between 1+ and 0 (P=0.19). Conversely, HER2 signal-intensity scores detected with the Cell Browser were: 3.69 (0), 4.38 (1+), 6.28 (2+) and 42.82 (3+). These results allow DEPArray Nxt to efficiently differentiate each single cell line, in particular HER2 1+ cells from both 0 and 2+ (P &amp;lt; 0.00001), enabling the collection of these specific cells. The area under the ROC was 0.7 and 0.72 (respectively 0 vs 1+ and 1+ vs 2+) and the optimal calculated cut-offs were 3.23 (lower) and 4.61 (higher). Conclusions HER2-low CTCs can be detected and separately collected using predetermined intensity cut-offs. Downstream single-cell or pooled collection can be subsequently performed. Further molecular characterizations, as DNA genome sequencing, could highlight the underlying altered pathways responsible for resistance to treatment and molecular patterns accountable for worse prognosis. Citation Format: Paolo D'Amico, Carolina Reduzzi, Wenan Qiang, Qiang Zhang, Lorenzo Gerratana, Ami N Shah, Andrew A Davis, Anthony Kang, Meilynn Shi, Youbin Zhang, Saya Jacob, Amir Behdad, Giuseppe Curigliano, Massimo Cristofanilli. Her2-low ctcs in breast cancer: Pipeline for phenotypic driven, single-cell collection and molecular analysis [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-02-06.

Multiplexed single-cell proteomics using SCoPE2.

Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying >1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Here we describe the Single Cell ProtEomics (SCoPE2) protocol, which uses an isobaric carrier to enhance peptide sequence identification. Single cells are isolated by FACS or CellenONE into multiwell plates and lysed by Minimal ProteOmic sample Preparation (mPOP), and their peptides labeled by isobaric mass tags (TMT or TMTpro) for multiplexed analysis. SCoPE2 affords a cost-effective single-cell protein quantification that can be fully automated using widely available equipment and scaled to thousands of single cells. SCoPE2 uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. The SCoPE2 workflow allows analyzing ~200 single cells per 24 h using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.

Tracking the fate and migration of cells in live animals with cell-cycle indicators and photoconvertible proteins

Cell migration and cell proliferation are the basic principles that make up a living organism, and both biologically and medically. In order to understand living organism and biological phenomena, it is essential to track the migration, proliferation, and fate of cells in living cells and animals and to clarify the properties and molecular expression of cells. Recent developments in novel fluorescent proteins have made it possible to observe cell migration and proliferation as the cell cycle at the single-cell level in living individuals and tissues. Here, we introduce cell cycle visualization of living cells and animals by Fucci (Fluorescent Ubiquitination-based Cell Cycle Indicator) system and in situ cell labeling of cells and tracking cell migration by photoactivatable and photoconvertible proteins. In addition, we will present our established methods as an example of combines above tools with single-cell molecular expression analysis to reveal the fate of migrating cells at single cell level.

Circulating tumor cell detection and single-cell analysis using an integrated workflow based on ChimeraX® -i120 Platform: A prospective study.

Circulating tumor cell (CTC) analysis holds great potential to be a noninvasive solution for clinical cancer management. A complete workflow that combined CTC detection and single-cell molecular analysis is required. We developed the ChimeraX® -i120 platform to facilitate negative enrichment, immunofluorescent labeling, and machine learning-based identification of CTCs. Analytical performances were evaluated, and a total of 477 participants were enrolled to validate the clinical feasibility of ChimeraX® -i120 CTC detection. We analyzed copy number alteration profiles of isolated single cells. The ChimeraX® -i120 platform had high sensitivity, accuracy, and reproducibility for CTC detection. In clinical samples, an average value of>60% CTC-positive rate was found for five cancer types (i.e., liver, biliary duct, breast, colorectal, and lung), while CTCs were rarely identified in blood from healthy donors. In hepatocellular carcinoma patients treated with curative resection, CTC status was significantly associated with tumor characteristics, prognosis, and treatment response (all P<0.05). Single-cell sequencing analysis revealed that heterogeneous genomic alteration patterns resided in different cells, patients, and cancers. Our results suggest that the use of this ChimeraX® -i120 platform and the integrated workflow has validity as a tool for CTC detection and downstream genomic profiling in the clinical setting.

Robotic Cell Printing for Constructing Living Yeast Cell Microarrays in Microfluidic Chips

Living cell microarrays in microfluidic chips allow the non-invasive multiplexed molecular analysis of single cells. Here, we developed a simple and affordable perfusion microfluidic chip containing a living yeast cell array composed of a population of cell variants (green fluorescent protein (GFP)-tagged Saccharomyces cerevisiae clones). We combined mechanical patterning in 102 microwells and robotic piezoelectric cell dispensing in the microwells to construct the cell arrays. Robotic yeast cell dispensing of a yeast collection from a multiwell plate to the microfluidic chip microwells was optimized. The developed microfluidic chip and procedure were validated by observing the growth of GFP-tagged yeast clones that are linked to the cell cycle by time-lapse fluorescence microscopy over a few generations. The developed microfluidic technology has the potential to be easily upscaled to a high-density cell array allowing us to perform dynamic proteomics and localizomics experiments.

Advancing Stem Cell Research through Multimodal Single-Cell Analysis.

Technological advances play a key role in furthering our understanding of stem cell biology, and advancing the prospects of regenerative therapies. Highly parallelized methods, developed in the last decade, can profile DNA, RNA, or proteins in thousands of cells and even capture data across two or more modalities (multiomics). This allows unbiased and precise definition of molecular cell states, thus allowing classification of cell types, tracking of differentiation trajectories, and discovery of underlying mechanisms. Despite being based on destructive techniques, novel experimental and bioinformatic approaches enable embedding and extraction of temporal information, which is essential for deconvolution of complex data and establishing cause and effect relationships. Here, we provide an overview of recent studies pertinent to stem cell biology, followed by an outlook on how further advances in single-cell molecular profiling and computational analysis have the potential to shape the future of both basic and translational research.

Multiplexed laser particles for spatially resolved single-cell analysis

Biomolecular analysis at the single-cell level is increasingly important in the study of cellular heterogeneity and its consequences, particularly in organismic development and complex diseases such as cancer. Single-cell molecular analyses have led to the identification of new cell types1 and the discovery of novel targets for diagnosis and therapy2. While these analyses are performed predominantly on dissociated single cells, emerging techniques seek understanding of cellular state, cellular function and cell–cell interactions within the native tissue environment by combining optical microscopy and single-cell molecular analyses. These techniques include in situ multiplexed imaging of fluorescently labeled proteins and nucleotides, as well as low-throughput ex vivo methods in which specific cells are isolated for downstream molecular analyses. However, these methods are limited in either the number and type of molecular species they can identify or the number of cells that can be analyzed. High-throughput methods are needed for comprehensive profiling of many cells (>1000) to detect rare cell types, discriminate relevant biomarkers from intrinsic population noise, and reduce the time and cost of measurement. Many established, high-throughput single-cell analyses are not directly applicable because they require tissue dissociation, leading to a loss of spatial information3. No current methods exist that can seamlessly connect spatial mapping to single-cell techniques. In this Perspective, we review current methods for spatially resolved single-cell analysis and discuss the prospect of novel multiplexed imaging probes, called laser particles, which allow individual cells to be tagged in tissue and analyzed subsequently using high-throughput, comprehensive single-cell techniques.

Abstract 1031: Single-cell analysis reveals a possibility of epithelial to circulating tumor cell transition (ECT) when tumor cells enter into the bloodstream

Abstract Tumor cells face the enviormental changes when leave tumor tissue enter into bloodstream. The environmental changes stimulate tumor cells to adapt the new enviorments with cell functional changes. Epithelial to mesenchymal transition (EMT) is well known and it explains the changes relatively in a portion of the circuating tumor cells (CTC) and in the relative later stage. We use the single-cell molecular analysis on house keeping genes, apoptosis genes, metabolism genes, Epithelial genes, EMT genes, metastasis genes, stem cell genes, and proliferation genes. The results reveal that less than half of individual CTCs express normal level of house keeping genes; apoptosis genes are not expressed at the normal level (reduced or not detectable) in the CTCs without house keeping genes expression; the expression of metabolism genes are relatively low especially in the CTCs without GAPDH expression; the expression level of Epithelial genes are low and the EpCAM and KRT7 are undetectable in most CTCs, but KRT8/18/19 are remaining high expression in the CTCs with GAPDH expressed; EMT genes of VIM, Twist1, MMP-2, TGFB1 are highly expressed in CTCs with GAPDH expressed but no or low expression in the CTCs without GAPDH expression; the expression of metastasis genes are relatively high in the CTCs with GAPDH expressed, but not in the CTCs without the expression of GAPDH; the expression of CD44, CD24, Bmi1, Oct-4, CXCR4, CD9, CXCL2, MAPK14 are highly expressed in the CTCs with GAPDH expressed but not in the CTCs without GAPDH expression; CD44 expressed in some CTCs with higher level than CD24, but much more individual CTCs (with GAPDH expressed) showed higher expression of CD24 than that of CD44 per single-cell level; the expression of proliferation genes are reduced in the CTCs with GAPDH expressed and not detectable in the CTCs without GAPDH expression. Based on the results, we hypthesize "Epithelial to circulating transition (ECT)" at the early stage after the tumor cells enter into bloodstream and followed by "CMT (circulating to mesenchymal transition and then MEC (mesenchymal to epithelial transition)". The ECT may includes the cell changes related to surviving, metabolism level, remaining the characteristics of metastatsis, stem cell signatures, Epithelial related genes and EMT related genes, proliferation genes and others. Studying the early changes of tumor cells enter into bloodstream maybe very improtant for gaining the understanding of the characteristics of survival cells and metastatic tumor cells and also important for basic research and clinical applications. Note: This abstract was not presented at the meeting. Citation Format: Glenn Deng, Stefanie Jeffrey. Single-cell analysis reveals a possibility of epithelial to circulating tumor cell transition (ECT) when tumor cells enter into the bloodstream [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1031.

Novel approaches for studying cell-mediated immune responses to influenza vaccination in humans

Abstract Vaccination is the most cost-effective public health intervention strategy in the prevention of the spread of infectious diseases. Unfortunately, each year, a substantial proportion of individuals do not respond or respond poorly to vaccination due to age, nutrition, pre-existing medical conditions, vaccine mismatch, or other unknown reasons. To investigate this further, we propose studying the mechanisms and molecular signatures associated with immunogenicity and the efficacy of influenza vaccination in different populations. The priming environment, induced by the innate immune system is crucial for initiating and fine-tuning antigen-specific adaptive immune responses. Comprehensive antibody panels have been developed to identify the new paradigms in the innate priming environment, focusing on NK, innate lymphoid cells and γδ T cells by flow cytometry in PBMC from vaccine recipients. The specific functions of these cells are then analyzed using single cell sorting and high-throughput transcriptomic and proteomics analysis. To further probe the adaptive response, we have successfully developed receptor binding site mutant HA (H1, H3, B) and HA stem (group 1 and 2) probes that are conjugated to fluorochromes to enumerate and characterize HA-specific B cells. M2e antigen probes are under development. Combining cell sorting, single cell molecular analyses, and the Illumina MiSeq system, paired heavy and light chains of B cell receptors (BCR) from isolated antigen specific B cells are sequenced to dissect antibody diversity. Through these novel approaches, we aim to identify and characterize critical host factors that can be exploited to develop as novel adjuvants and strategies for more effective influenza vaccines.